def verify():
from tvm.contrib import tedd
str = tedd.viz_itervar_relationship_graph(s, False, '', True)
findany(r"digraph \"IterVar Relationship Graph\"", str)
findany(r"subgraph cluster_legend", str)
# Check subgraphs for stages
findany(r"subgraph cluster_Stage_0", str)
findany(r"subgraph cluster_Stage_1", str)
# Check itervars and their types
findany(r"i\(kDataPar\)\<br/\>range\(min=0, ext=n\)", str)
findany(r"k\(kCommReduce\)\<br/\>range\(min=0, ext=m\)", str)
# Check the split node
findany(r"Split_Relation_1_0 +.+\>Split", str)
# Check all edges to/from the split node
findany(r"IterVar_1_1:itervar -> Split_Relation_1_0:Input", str)
findany(r"Split_Relation_1_0:Outer -> IterVar_1_2:itervar", str)
findany(r"Split_Relation_1_0:Inner -> IterVar_1_3:itervar", str)
# IterVar type with the index box color, shown in the legend. # # If a stage doesn't compute_at any other stage, it has an edge directly to the # ROOT node. Otherwise, it has an edge pointing to the IterVar it attaches to, # such as W.shared attaches to rx.outer in the middle compute stage. # ###################################################################### # .. note:: # # By definition, IterVars are internal nodes and computes are leaf nodes in # a schedule tree. The edges among IterVars and compute within one stage are # omitted, making every stage a block, for better readability. # tedd.viz_itervar_relationship_graph(s, dot_file_path="/tmp/itervar.dot") # tedd.viz_itervar_relationship_graph(s, show_svg = True) ###################################################################### # .. image:: https://github.com/dmlc/web-data/raw/master/tvm/tutorial/tedd_itervar_rel.png # :align: center # # The last one is an IterVar Relationship Graph. Every subgraph represents a # stage and contains IterVar nodes and transformation nodes. For example, # W.shared has three split nodes and three fuse nodes. The rest are IterVar # nodes of the same format as the IterVar rows in Schedule Trees. Root # IterVars are those not driven by any transformation node, such as ax0; leaf # IterVars don't drive any transformation node and have non-negative indices, # such as ax0.ax1.fused.ax2.fused.ax3.fused.outer with index of 0. #
